TECHNICAL AND ECONOMIC FEASIBILITY OF OFF-GRID PHOTOVOLTAIC SYSTEMS FOR IRRIGATION

ABSTRACT In rural areas, the electricity supply is affected by problems such as low quality and limited access in some regions. The use of renewable sources, with decentralized generation, can offer an alternative to the existing scenario. The objective of this work is to perform a technical and economic analysis of off-grid photovoltaic systems, without energy storage, intended for irrigation. Photovoltaic systems from different irrigation systems were sized, with power ratings from 0.736 to 29.44 kW. Their technical feasibility was determined based on the energy supply period and the availability of solar radiation as restriction variables. Economic feasibility was determined by the indicators of net present value (NPV), internal rate of return (IRR), benefit/cost ratio (B/C) and profitability index (PI). Feasible operation was found for irrigation systems with motors up to 11.04 kW; however, for systems that required higher powers, the number of operating hours available was less than the minimum required. NPV, IRR, B/C and PI showed increasing values as a function of increasing power. Thus, off-grid photovoltaic systems without energy storage are technically and economically feasible for systems with power of up to 11.04 kW

THE USE OF ARTIFICIAL INTELLIGENCE FOR ESTIMATING SOIL RESISTANCE TO PENETRATION

<div><p>ABSTRACT The aim of this study was to present and to evaluate methodologies for the estimation of soil resistance to penetration (RP) using artificial intelligence prediction techniques. In order to do so, a data base with values of physical-water characteristics of the soils available in the literature was used, and the performances of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were evaluated. The models generated from the ANNs were implemented through the multilayer perceptron with backpropagation algorithm of Matlab software, varying the number of neurons in the input and intermediate layers. For the procedure from SVM, the RapidMiner software was used, varying input variables, the kernel function and the coefficients of these functions. The efficiency of the techniques was analyzed by the ratio 1:1, and later, compared to the Busscher non-linear model (Busscher, 1990). The results showed that the artificial intelligence models (ANN and SVM) are efficient and have predictive capacity superior to the Busscher model, under data conditions of soils with textural classes and different, and similar managements, although with higher performance index values for conditions of soils of the same textural class exposed to the same management.</p></div

Performance of explicit approximations of the coefficient of head loss for pressurized conduits

ABSTRACT One of the parameters involved in the design of pressurized hydraulic systems is the pressure drop in the pipes. The verification of the pressure drop can be performed through the Darcy-Weisbach formulation, which considers a coefficient of head loss (f) that can be estimated by the implicit Colebrook-White equation. However, for this determination, it is necessary to use numerical methods or the Moody diagram. Because of this, numerous explicit approaches have been proposed to overcome such limitation. In this sense, the objective of this study was to analyze the explicit approximations of the f for pressurized conduits in comparison to the Colebrook-White formulation, determining the most precise ones so that they can be used as an alternative solution that is valid for the turbulent flow regime. Twenty nine explicit equations found in the literature were analysed, determining the f through the Reynolds number in the range of 4 × 103 ≤ Re ≤ 108 and a relative roughness (Ɛ/D) of 10-6 ≤ Ɛ/D ≤ 5 × 10-2, and obtaining 160 points for each equation. The performance index and relative error of the formulations were analyzed in relation to the Colebrook-White equation. Considering the equations analyzed, we found seven that presented excellent performance and high precision, highlighting the formulation of Offor & Alabi, which can be used as an alternative to the Colebrook-White standard equation

Economically optimal water depth and grain yield of common bean subjected to different irrigation depths

ABSTRACT Common bean crop plays an important role in the world, not only in economic aspects but also in social development. The objective of this study was to evaluate the grain yield and the economically optimal water depth which reflects the maximum technical efficiency of the common bean crop. The experiment was conducted in greenhouse, in Alegrete - RS, from February to May 2016. A completely randomized design was used, consisting of five water replacement treatments (25, 50, 75, 100 and 125% crop evapotranspiration - ETc) and four replicates. Based on the obtained results, both water deficit and water excess directly affected the final grain yield of the crop. Maximum grain yield was 3,554.1 kg ha-1, obtained by applying 492.72 mm (100% ETc). On the other hand, the economically optimal water depth was estimated at 91.2% ETc, indicating that water depths above this value are not suitable for maximum technical efficiency in the common bean crop under these conditions. It was concluded that the water depth equivalent to 100% ETc maximizes grain yield for the region of Alegrete-RS, and irrigation is considered a solution in the water supply to the common bean crop during critical periods